Segment scene in new domain using features from diffusion models with DIFF
Segment scene in new domain using features from diffusion models with DIFF
Diffusion Features to Bridge Domain Gap for Semantic Segmentation
arXiv paper abstract https://arxiv.org/abs/2406.00777
arXiv PDF paper https://arxiv.org/pdf/2406.00777
… study … utilization of the implicit knowledge embedded within diffusion models to address challenges in cross-domain semantic segmentation.
This paper investigates the approach that leverages the sampling and fusion techniques to harness the features of diffusion models efficiently.
Contrary to the simplistic migration applications characterized by prior research, … multi-step diffusion process inherent in the diffusion model manifests more robust semantic features.
… propose DIffusion Feature Fusion (DIFF) as a backbone use for extracting and integrating effective semantic representations through the diffusion process.
By leveraging the strength of text-to-image generation capability, … introduce a new training framework designed to implicitly learn posterior knowledge from it.
… methodology surpasses preceding approaches in mitigating discrepancies across distinct domains and attains the state-of-the-art (SOTA) benchmark.
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